## produce graph
annual_juvenile_graph <- ggplot(data = juvenile_table, aes(x = year, y = count)) +
geom_bar(color = "coral4", fill = "coral3", stat = "identity")+
scale_x_continuous(breaks = 1999:2012)+
scale_y_continuous(limits=c(0, 130), breaks = c(0, 25, 50, 75, 100, 125))+
theme_light()+
labs( x = "Year", y = "Number of Juvenile Hare Traps", title = "Annual Juvenile Hare Trap Counts", subtitle = "1999-2012")+
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
axis.title.x = element_text(vjust = 0.2))
annual_juvenile_graph
Figure 1: Annual juvenile hare trap counts-
The data visualization clearly shows that there is a huge variation between years in the number of juvenile hares that were collected. The max was 126 in 1999 and